Tracking noncooperative space-object clusters couples observation duration, revisit timing, and shared constellation resources. We develop a scheduler that constrains position–velocity covariance throughout a 200 s measurement-free interval after each observation. Variable-duration visits combine time-dependent common-field acquisition, serial laser ranging, and independent target posteriors. A hierarchical differential-evolution search coordinates these visits. Nonlinear truth and an extended Kalman filter evaluate all targets in eight synthetic scenes with 72 observers and 200 Monte Carlo realizations per target. Six matched methods, five paired search seeds, and duration and budget scans separate scheduling effects. Under the reference condition, initialization-priority adaptive duration (IP-AD) gives position and velocity root-mean-square errors of 18,443.8 ± 1432.6 m and 57.102 ± 6.491 m/s. Uncertainty is the sample standard deviation of five eight-scene means. Relative to fixed 20 s visits with identical initialization priority and hold screening, the means decrease by 66.00% and 46.46%. However, relaxed planning thresholds combined with lower measurement noise reverse this benefit. Adaptive duration therefore offers conditional average gains; covariance-feasible plans do not ensure that every target meets the actual-error requirements.
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Feng et al. (2026) studied this question.
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